无需训练即可修改梅尔声谱的音高，适配任意梅尔基神经语音合成器。
Pseudo-Cepstrum: Pitch Modification for Mel-Based Neural Vocoders
- 在倒谱域直接移动谐波峰值实现音高变换。
- 在多个先进神经声码器上验证，音质保持良好且主观评分领先。
- 兼容所有梅尔基声码器，无需额外训练或模型改动。
本文提出一种基于倒谱的音高修改方法，适用于任何梅尔频谱表示。该方法无需额外训练或修改模型，可与任意梅尔基声码器兼容。通过将梅尔频谱经伪逆梅尔变换得到幅度谱，再应用DCT转换至倒谱域，直接移动倒谱峰位置，随后通过IDCT与梅尔滤波组重构新梅尔频谱。生成的音高调整后梅尔频谱可由任意兼容声码器合成语音。实验在多种先进神经声码器上进行，结合客观与主观评估，结果表明该方法在音质和音高准确性上优于传统方法。
原文摘要 · Abstract (English)
This paper introduces a cepstrum-based pitch modification method that can be applied to any mel-spectrogram representation. As a result, this method is compatible with any mel-based vocoder without requiring any additional training or changes to the model. This is achieved by directly modifying the cepstrum feature space in order to shift the harmonic structure to the desired target. The spectrogram magnitude is computed via the pseudo-inverse mel transform, then converted to the cepstrum by applying DCT. In this domain, the cepstral peak is shifted without having to estimate its position and the modified mel is recomputed by applying IDCT and mel-filterbank. These pitch-shifted mel-spectrogram features can be converted to speech with any compatible vocoder. The proposed method is validated experimentally with objective and subjective metrics on various state-of-the-art neural vocoders as well as in comparison with traditional pitch modification methods.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。